1. ASSESSMENT OF YIELD LOSS BY PLANT PATHOGENS

2. ■ For making decision concerning the need of disease management (cost/effective calculations ■ For identifying the time when control is needed and assisting to develope effective management procedures. Why do we need to assess yield loss? What are the uses of yield loss records

3. ■ For administrative decisions: making priorities in research, breeding, allocation of efforts, etc. ■ For insurance purposes

4. Loss assessments can be made on several scales ■ Individual plants ■ Small plots (e.g., experimental plots) ■ Individual field ■ Regions ■ Nations ■ The entire world

5. How plant pathogens affect their hosts ? Effects on host physiology Effects on host development Effects on yield quantity Effects on yield quality Leaf infection

6. Effects on host physiology

7. Effects of plant pathogens on host physiology Effects of radiation interception (RI) Effects of radiation use efficiency (RIE) reflected radiation intercepted radiation transmitted radiation

8. Effects of plant pathogens on host physiology Effects of radiation interception Stand reducers Seedling diseases

9. Effects of plant pathogens on host physiology Effects of radiation interception Tissue consumers Alternaria macrospora in cotton

10. Effects of plant pathogens on host physiology Effects of radiation interception Leaf senescence accelerators Alternaria solani in tomatoes

11. Effects of plant pathogens on host physiology Effects of radiation interception Light “stealers” Smutty mold (Aspergillus sp.) in cotton

12. Disease severity (%) Photosynthesis rate (%) 050100 0 50 100 invaded area infected area Necrotic area Effects of plant pathogens on host physiology Effects of radiation use efficiency photosynthetic rate reducers

13. Effects of plant pathogens on host physiology Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 stomata Alternaria stomata

14. Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 Powdery mildew stomata

15. Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 rusts stomata rust pustules

16. Effects of radiation use efficiency assimilate suppers Powdery mildews

17. Quantification of yield losses

18. Effects of Alternaria macrospora on cotton yield (mean of 11 field experiments) Treatmentyield (t/ha)yield increment t/ha% Untreated Maneb 4.26 5.03 - 0.78 - 15.4 Tebuconazole5.701.4425.2

19. Measurement of yield loss: which reference to use? Commercially managed-plot yield (t/ha) Untreated-plot yield 3.0 5.0 Attainable yield 8.0 Potential yield 15.0 -40% +66% Healthy-plot yield 6.0 -50% +100%

20. Measurement of yield loss: what is the reference? Differences between yield of a reference plot and yield of a diseased plot Loss = [yield of reference plot] - [yield of diseased plot] Reference plots: A non-infected (healthy) plot The least infected plot in the experiment Average yield of commercial plot in the area

21. Measurement of yield loss: what is the reference? Differences between estimated yield of a healthy plot and yield of a diseased plot Loss = [estimated yield of healthy plot] - [yield of diseased plot] Disease severity (%) Yield (t/ha) 0100

22. The damage function The quantitative relationship between disease intensity and yield (or yield loss) Disease intensity ( %) Yield (t/ha) Disease intensity ( %) Yield loss (%)

23. The damage function Disease intensity Yield Linear Disease intensity Yield Logarithmic Disease intensity Yield Compensation Disease intensity Yield Optimum

24. The relationship between the time of disease development and the resultant yield loss

25. Yield components of cereals Emergence Tillering Boot stage Grain filling

26. Yield components of cereals no. of spikelets per ear no. of spikelets per unit area no. of grains per spikelet no. of grains per unit area Yield per unit area weight of a grain no. of plants per unit area no. of ears per plant no. of ears per unit area

27. The yield components that are affected by plant diseases are those that are created at, or soon after, the time of disease onset % difference No. of ears/plant No. spikelets/ear Grain wt. Yield 19.1* 7.6 4.2 28.5* Growth stage tillering Disease severity (%) untreated sprayed emergence Effects of powdery mildew in barley on yield and its components

28. milk Growth stage tillering Disease severity (%) Effects of Septoria tritici blotch in wheat on yield and its components untreated sprayed earing % difference No. of ears/plant No. spikelets/ear No. grains/spikelet Grain weight Yield 2.5 0.8 8.1* 8.0* 18.1*

29. In Israel, Septoria tritici blotch in wheat affects only the weight of individual grains. Thus, there is no need to control the disease before the earing stage. Similarly, the is no need to control the disease after most of the grain weight was accumulated.

30. Yield components of a board-leaf plant Emergence Vegetative growth Reproductive growth Yield production

31. Yield components of a broad-leaf plant weight of individual fruit Yield per unit area no. of plants per unit area no. of fruits per plant no. of fruits per unit area

32. Effects of Alternaria in cotton on yield and its components Boll weightBoll Number untreated sprayed Yield

33. A. macrospora affect only the number of bolls per plant. Bolls are shed only at the initial stages of their development. Thus, disease management is very important early in the season when the bolls are small, but not towards the end of the season, when the bolls had already developed enough.

34. Yield loss models

35. The critical point model Disease severity at time G1 (%) Yield (t/ha) Time Disease severity (%) G1 harvest disease assessment Y =  0 -  1 X Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 = reduction in yield for each percent increase in disease severity X = disease severity of the diseased plot

36. The critical point model is used mainly in cereals. In cereals have distinct growth stages and it is possible to determine precisely which crop growth stage is affected most by the disease. This stage should be chosen to be the “critical” stage - for assessment. Critical point models are used mainly for “after- season” loss assessment. Uses of critical point models

37. The multiple point model Time Disease severity (%) T1T2T3T4T5T6T7T8 Y =  0 -  1 X 1 -  2 X 2 -  3 X 3 -  4 X 4 -  5 X 5 -  6 X 6 -  7 X 7 -  8 X 8 Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 -  8 = reduction in yield in each sampling for each percent increase in disease severity X 1 -X 8 = disease severity of the diseased plot in each date harvest disease assessments

38. ■ The multiple point model is used mainly in broad- leaf crops. ■ In broad-leaf crops yield is accumulated during a long period and there are no distinct growth stages. ■ In many cases, the disease affect yield during the whole period of its accumulation. Uses of multiple point models

39. Time Disease severity (%) T1T2T3T4 Critical severity The critical time model Time for critical severity (days) Yield (t/ha) Y =  0 +  1 X Y = yield of a diseased plot  0 = estimated yield of a plot infected at day 0  1 =increase in yield for each day of delay in time to critical severity X = time for critical severity in diseased plot

40. Critical time models may be used in both cereals and broad-leaf crops. These models are applicable in situations where disease onset vary markedly from year to year and from location to location. The critical time models may be used for decision making. For that purpose, the critical severity level to be used should be low enough, to enable proper disease suppression. Uses of critical time models

41. The Area Under the Disease Progress Curve (AUDPC) model Time Disease severity (%) AUDPC (Disease*days) Yield (t/ha) Y =  0 -  1 X Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 =decrease in yield for each increase in AUDPC unit X = AUDPC units

42. The AUDPC models are used in both broad- leaf and cereal crops. In most cases, a very good relationship exist between AUDPC values and yield. The AUDPC models are used mainly for “after-season” loss assessment. Uses of the AUDPC models

43. Measure Disease Progression 1. Research rules and guidelines that apply to measuring the specific disease and crop you investigate. The required size of the plant sample varies by crop and disease. Studying late blight in tubers, for example, requires a minimum sample of 40 plants. 2.Plant the appropriate number of plants required for the study.

44. 3.Watch carefully for signs of the disease. Research when signs are expected to occur so that you are prepared. For example, signs of late blight occur about 30 to 40 days after planting and 10 days after the last application of fungicide. 4.Estimate visually the percentage of infected leaf area in your sample as soon as you notice the disease.

45. 5. Record the percentage of infected leaf area at regular time intervals. Researchers take reading for late blight every seven days if the disease progresses more quickly than expected. Readings are taken every 14 days when disease progression is slower. 6.Stop recording infection measurements when the percentage of infection stops increasing, and the disease progression levels.

46. 7.Add the first two infection percentages you recorded. 8.Divide the addition result by two to find the average or mid-value of the two readings. 9.Multiply the average or mid-value by the time interval, which is the number of days from the first reading to the second reading. If you took the first reading on day 20 and the second reading on day 27, for example, then the number of days, or time interval, is seven days. 10.Record the result in units of percentage days. The value is an area of a trapezoid.

47. 11.Repeat Steps One through Four for the second and third infection readings you took. Their result will be the area of a second trapezoid. Repeat Steps One through Four until you calculated trapezoid areas for all readings. 12.Add all of the trapezoids to find the AUDPC. Lower AUDPCs represent slower disease progression and greater resistance to the disease. Higher AUDPCs represent faster disease progression and higher susceptibility to the disease.

48. Concluding remarks Losses may be predicted early in the season for management decision making or after the season for general analyses. Plant pathogens may affect the physiology of the host and result in yield losses directly or indirectly. Determination of the yield component to be affected by the disease is an important component of an IPM strategy. Yield loss should be determined in relation to a reference plot. Yield loss may be quantified by several models: the critical point model, the multiple point model, the critical time model and the AUDPC model.

49. Important points 1.Critical times tillering, stem elongation, flag leaf opening 2.Crop loss : kernel weight 3.Crop loss is a function of disease epidemic L = 1230.91+1.37AUDPC